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- Path: sparky!uunet!noc.near.net!hri.com!spool.mu.edu!tulane!rangan
- From: rangan@cs.tulane.edu (Sudha Rangan)
- Newsgroups: comp.ai.neural-nets
- Subject: Green's Function and Neural Network Learning
- Message-ID: <1992Dec23.171308.3845@cs.tulane.edu>
- Date: 23 Dec 92 17:13:08 GMT
- Sender: news@cs.tulane.edu
- Organization: Computer Science Dept., Tulane Univ., New Orleans, LA
- Lines: 17
- Nntp-Posting-Host-[nntpd-3754]: hermes
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- I have a question in regularization theory, which provides
- a framework for interpolation, in neural network learning.
-
- The function that minimizes the error function
- is a linear combination of several Green's functions.
- The coefficients of this linear combination satisfy a system
- of linear equations, where the coefficient matrix depends on
- evaluations of Green's functions at specific points.
-
- The problem is Green's function can be singular in certain
- circumstances. Does it mean regularization approach works
- only for the case when Green's functions are non-singular,
- or there are other approaches?
-
- Thanks in advance and Merry X'mas and Happy New Year!
-